Verified against Claude · 2026-07-27
Turn a raw webinar or interview transcript into a structured blog post
Restructures a spoken transcript into a written argument built around its actual best insights rather than chronological order, keeping every direct quote verbatim and flagging anything that needs speaker confirmation before publish.
The prompt
Ready to copy — highlighted parts are example details you can swap.
You are converting a raw transcript — a webinar, podcast, or interview — into a structured blog post. Spoken language and written argument have different shapes; your job is to find the real structure inside the transcript's chronological mess, not just clean up the sentences in the order they were said.
TRANSCRIPT EXCERPT
A 45-minute webinar transcript on API rate limiting, where the strongest concrete example — a specific incident where a naive retry loop caused a cascading outage — comes up in the Q&A at minute 38, not in the prepared talk.
SPEAKER CREDENTIALS
Staff engineer at a payments company, led the incident response for the outage referenced in the talk
KEY MOMENTS
Minute 12 (why exponential backoff alone isn't enough), minute 38 (the cascading outage story from Q&A), minute 41 (the specific jitter formula they now use)
TARGET ANGLE
Framed as "the retry mistake that caused a real outage," not a general rate-limiting explainer.
AUDIENCE
Backend engineers who already know what rate limiting is and want the specific failure mode, not a 101 explainer.
TARGET LENGTH
1,200-1,400 words
CONVERSION RULES
Identify the two or three actual best insights in the transcript based on the key moments flagged, and restructure the post around those, in whatever order builds the strongest written argument — not in the order they happened to come up in conversation, since a live talk's best point is often buried in an answer to an unrelated audience question near the end, and a post that follows chronological order will bury it there too. Strip filler that only exists because the source was spoken — false starts, "you know," "so, like I said," mid-sentence self-corrections — but preserve the actual substance and phrasing of what the speaker said whenever quoting them directly. When quoting the speaker, use their exact words, verbatim, without smoothing grammar or sharpening the phrasing to sound more polished — if a quote needs cleanup to be readable, either use "..." to mark an omission of filler words within it, or don't present it as a direct quote at all and instead attribute the idea to them in the surrounding prose. Add context the live audience had but a blog reader won't — a reference to a slide that isn't visible in text, a callback to something said ten minutes earlier ("as I mentioned") that a reader skimming the post has no way to have seen — spell out what was being referenced rather than leaving the callback dangling. Do not silently resolve an inaudible or ambiguous moment in the transcript by guessing what the speaker probably meant; flag it explicitly as needing speaker confirmation before publish, and write around it in a way that doesn't depend on the guessed content being correct. Credit the speaker using their actual stated credentials, not an inflated or vaguer version of them.
OUTPUT FORMAT
1. The structured post, with headings organized around the identified best insights, not the transcript's chronological order.
2. A short note on how the post's structure differs from the transcript's original order, and why the reordering serves the argument.
3. A list of every direct quote used, each one flagged as either verbatim or trimmed-with-ellipsis.
4. Anything flagged as needing speaker confirmation before publish, quoting the exact ambiguous or inaudible passage.Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
Restructuring around the identified best insights instead of chronological order addresses the core structural mismatch between a spoken talk and a written post: a live speaker builds toward points gradually, answers audience questions in whatever order they're asked, and often delivers their single best concrete example in response to a question near the end rather than in the prepared material — a transcript-to-post conversion that just cleans up sentences in original order inherits that same buried structure, producing a post where the strongest material is stuck in paragraph nine instead of leading the piece. The verbatim-quoting rule, with an explicit ellipsis convention for trimming filler rather than silent smoothing, matters because a quote attributed to a named, credentialed person carries a factual claim about what that person actually said — polishing a quote's grammar while still presenting it in quotation marks misrepresents the speaker's actual words under their own name, which is a different and more serious problem than simply writing awkward prose, and the ellipsis convention gives a legitimate way to remove genuine filler ("um," a false start) without crossing into fabricating cleaner language the person didn't say. Explicitly flagging inaudible or ambiguous moments instead of guessing addresses a failure mode specific to transcript work that a general editing pass wouldn't catch: transcription errors and unclear audio are common, and a model asked to "write a clean post from this transcript" will often silently resolve an ambiguous phrase to whatever reading makes the surrounding sentence make sense grammatically, which can quietly put words in a real, named speaker's mouth that they never actually said — flagging it for confirmation instead keeps that risk visible rather than hidden inside otherwise-clean prose. Requiring context to be added for callbacks the original live audience had but a blog reader wouldn't (a reference to an unseen slide, an "as I mentioned" pointing at something said much earlier) targets a real comprehension gap: a talk's internal references work because the audience experienced the whole thing linearly and recently, while a blog reader may jump straight to a specific section, and an unresolved callback in text reads as a non sequitur rather than the natural echo it was in the room.
Verified against
Claude Claude Sonnet 5 · 2026-07-27
ChatGPT GPT-5.1 · 2026-08-02
Changelog
- 2026-07-27 — Initial publish, verified against Claude (Claude Sonnet 5) and ChatGPT (GPT-5.1).
Need this built into your business?
If a prompt isn't enough — SEO, built and maintained for you — that's Scult's day job.
EXPLORE SEO
